Tampa Bay load estimates

Loading estimates for major pollutants and hydrologic inputs to Tampa Bay. Estimates are tons per year and are unique to each major bay segment. All estimates from Janicki Environmental. Source content here.

Total Nitrogen

Plot

cols <- qualitative_hcl(length(levs), palette = "Dynamic")

for(lev in seq_along(levs)){
  
  toplo <- tndat %>% 
    filter(bay_segment %in% !!levs[lev]) %>% 
    spread(SOURCE, TN_tons)

  showleg <- F
  if(lev == 1)
    showleg <- T
  
  p <- plot_ly(toplo)  %>% 
    add_markers(x = ~YEAR, y = ~NPS, color = I(cols[5]), stackgroup = 'one', mode = 'none', marker = list(opacity = 0, size = 0), 
                        showlegend = showleg, legendgroup = 'grp5', name = 'NPS') %>%   
    add_markers(x = ~YEAR, y = ~IPS, color = I(cols[4]), stackgroup = 'one', mode = 'none', marker = list(opacity = 0, size = 0), 
                        showlegend = showleg, legendgroup = 'grp4', name = 'IPS') %>% 
    add_markers(x = ~YEAR, y = ~GWS, color = I(cols[3]), stackgroup = 'one', mode = 'none', marker = list(opacity = 0, size = 0), 
                        showlegend = showleg, legendgroup = 'grp3', name = 'GWS') %>% 
    add_markers(x = ~YEAR, y = ~DPS, color = I(cols[2]), stackgroup = 'one', mode = 'none', marker = list(opacity = 0, size = 0), 
                        showlegend = showleg, legendgroup = 'grp2', name = 'DPS') %>% 
    add_markers(x = ~YEAR, y = ~AD, color = I(cols[1]), stackgroup = 'one', mode = 'none', marker = list(opacity = 0, size = 0), 
                        showlegend = showleg, legendgroup = 'grp1', name = 'AD') %>% 
    add_annotations(
      text = ~unique(bay_segment),
      x = 0.5,
      y = 1.2,
      yref = "paper",
      xref = "paper",
      xanchor = "middle",
      yanchor = "top",
      showarrow = FALSE,
      font = list(size = 15)
    )
  
  if(lev == 3)
    p <- p %>% 
      layout(
        yaxis = list(title = 'Total Nitrogen (tons/yr)')
      )
  
  if(lev != 3)
    p <- p %>% 
    layout(
      yaxis = list(title = NA)
    )
  
  nm <- paste0('p', lev)
  
  assign(nm, p)
  
}

subplot(p1, p2, p3, p4, p5, shareX = T, nrows = length(levs), shareY = F, titleY = T) %>%
  layout(
    xaxis = list(title = NA, gridcolor = '#FFFFFF'),
    barmode = 'stack',
    legend = list(title = list(text = 'Source'))
  )

Table

totab <- tndat %>% 
  select(bay_segment, YEAR, SOURCE, TN_tons) %>% 
  pivot_wider(names_from = SOURCE, values_from = TN_tons) %>% 
  rowwise() %>% 
  mutate(Total = sum(AD, DPS , IPS, NPS ,GWS, na.rm = T)) %>% 
  ungroup()

totab %>%
  downloadthis::download_this(
    output_name = "TN-load-data",
    output_extension = ".csv",
    button_label = "Download data",
    button_type = "warning",
    has_icon = TRUE,
    icon = "fa fa-save"
  )

Download data

sticky_style <- list(position = "sticky", left = 0, background = "#fff", zIndex = 1,
                       borderRight = "1px solid #eee", fontWeight = 'bold')
tab <- reactable(totab,
                   groupBy = 'bay_segment',
                   columns = list(
                     YEAR = colDef(name = 'Year', 
                                   format = colFormat(digits = 0, separators = FALSE), 
                                   style = sticky_style, 
                                   headerStyle = sticky_style, 
                                   footerStyle = sticky_style
                                   ), 
                     bay_segment = colDef(name = ''), 
                     Total = colDef(
                        class = "sticky right-col-1", 
                        headerClass = "sticky right-col-1",
                        footerClass = "sticky right-col-1"
                     )
                   ),
                   defaultColDef = colDef(
                     footerStyle = list(fontWeight = "bold"),
                     format = colFormat(digits = 2, separators = TRUE),
                     resizable = TRUE
                     )
)
tab